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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Коррупция «одного окна»: теория и эмпирический анализ

Вопросы экономики. 2018. № 9. С. 32–51.
Polishchuk L., Rubin A., Кочнев Р. Ю.

We present comparative analysis of the impact of centralized and decentralized corruption for private sector. Theory and empirical evidence point out to a «double jeopardy» of decentralized corruption which increases the burden of corruption upon private sector firms and weakens the incentives of bureaucracy to provide public production inputs, such as infrastructure. These outcomes are produced by simultaneous free-riding and the tragedy of the commons effects. The empirical part of the paper utilizes data of the Business Environment and Enterprise Performance project.

Priority areas: economics
Language: Russian
Full text
Keywords: коррупцияcorruptionроссийские регионыTragedy of the Commons Russian regionsадминистративный режимadministrative regimeтрагедия общиныэффект безбилетника
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